| Today's News and Trends | Few radiologists understand the relationship between radiology and artificial intelligence (AI) quite like Keith Dreyer, DO, PhD, vice chairman and associate professor of radiology at Massachusetts General Hospital in Boston. Few radiologists understand the relationship between radiology and artificial intelligence (AI) quite like Keith Dreyer, DO, PhD, vice chairman and associate professor of radiology at Massachusetts General Hospital in Boston. | | |
| Researchers have developed a novel technique that reconstructs medical images using artificial intelligence (AI) and machine learning, according to a new study published in Nature. This saves radiologists valuable time and could potentially result in patients being exposed to lower radiation doses. Researchers have developed a novel technique that reconstructs medical images using artificial intelligence (AI) and machine learning, according to a new study published in Nature. This saves radiologists valuable time and could potentially result in patients being exposed to lower radiation doses. | | |
| Artificial intelligence (AI) technologies had a significant presence at the European Society of Radiology’s annual meeting, the European Congress of Radiology (ECR) 2018. According to a new report published by Signify Research, however, the buzz wasn’t as strong as it was at RSNA 2017 in Chicago. Artificial intelligence (AI) technologies had a significant presence at the European Society of Radiology’s annual meeting, the European Congress of Radiology (ECR) 2018. According to a new report published by Signify Research, however, the buzz wasn’t as strong as it was at RSNA 2017 in Chicago. | | |
| Researchers used machine learning techniques to confirm that radiomic imaging features of breast tumors extracted from digital mammography are associated with breast cancer subtypes, according to a new study published in Academic Radiology. Researchers used machine learning techniques to confirm that radiomic imaging features of breast tumors extracted from digital mammography are associated with breast cancer subtypes, according to a new study published in Academic Radiology. | | |
| Forty-seven percent of healthcare organizations are either already using artificial intelligence (AI) to help with medical imaging or actively planning to use AI, according to a new report published by KLAS. And adoption is expected to escalate sooner than later. Forty-seven percent of healthcare organizations are either already using artificial intelligence (AI) to help with medical imaging or actively planning to use AI, according to a new report published by KLAS. And adoption is expected to escalate sooner than later. | | |
| Convolutional neural networks (CNNs) can be trained to analyze visual imagery much easier than other artificial neural networks, making their capabilities especially important to the future of radiology, according to a new analysis published in Current Problems in Diagnostic Radiology. Convolutional neural networks (CNNs) can be trained to analyze visual imagery much easier than other artificial neural networks, making their capabilities especially important to the future of radiology, according to a new analysis published in Current Problems in Diagnostic Radiology. | | |
| A team of California researchers has developed a method for predicting the responses of obsessive compulsive disorder (OCD) patients to cognitive behavioral therapy using machine learning and fMRI, according to work published in the journal PNAS. A team of California researchers has developed a method for predicting the responses of obsessive compulsive disorder (OCD) patients to cognitive behavioral therapy using machine learning and fMRI, according to work published in the journal PNAS. | | |
| Radiologists must step up and get involved with the design and development of AI tools relevant to radiology, according to a new column published in the Journal of the American College of Radiology. By just taking a “wait and see” approach, specialists risk being left out of the conversation altogether. Radiologists must step up and get involved with the design and development of AI tools relevant to radiology, according to a new column published in the Journal of the American College of Radiology. By just taking a “wait and see” approach, specialists risk being left out of the conversation altogether. | | |
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